With the development of technology, artificial intelligence and big data have brought a new research strategy to psychology research. Compared with traditional methods, the combination of artificial intelligence and big data produces three advantages of ecological data:vertical tracking, time backtracking, high internal and external validity. This kind of interpersonal interaction based on Online Social Networking has profoundly affected or even changed people's psychological and behavioral characteristics. Meanwhile, ecological behavior data can be used, combined with other artificial intelligence technology, to establish a psychological index prediction model to achieve automatic identification of people's psychological indicators. This paper discusses the application of artificial intelligence and big data in psychological research and practice by taking personality prediction model, Proactive Suicide Prevention Online, and Qingdao prawn as examples. Finally, when using big data to analyze relevant psychological indicators, we must also pay attention to protecting user privacy and rational use of big data and artificial intelligence technology.
LIU Xingyun
,
LIU Xiaoqian
,
XIANG Yuanyuan
,
ZHU Tingshao
. Artificial intelligence and big data as applied to Psychology[J]. Science & Technology Review, 2019
, 37(21)
: 105
-109
.
DOI: 10.3981/j.issn.1000-7857.2019.21.010
[1] 梁宁建. 心理学导论[M].上海:上海教育出版社, 2006.
[2] Gosling S D, Augustine A A, Vazire S, et al. Manifestations of personality in online social networks:Self-reported facebook-related behaviors and observable profile information[J]. Cyberpsychology Behavior and Social Networking, 2011, 14(9):483-488.
[3] Zhou Y, Zhang L, Liu X, et al. Predicting the trends of social events on Chinese social media[J]. Cyberpsychology Behavior and Social Networking, 2017, 20(9):533-539.
[4] Conroy M, Feezell J T, Guerrero, M. Facebook and political engagement:A study of online political group membership and offline political engagement[J]. Computers in Human behavior, 2012, 28(5):1535-1546.
[5] Matz S C, Kosinski M, Nave G, et al. Psychological targeting as an effective approach to digital mass persuasion[J]. Proceedings of the National Academy of Sciences, 2017, 114(48):12714-12719.
[6] Liu M M, Xue J, Zhao N, et al. Using social media to explore the consequences of domestic violence on mental health[J]. Journal of Interpersonal Violence, 2018:1-21.
[7] 彭聃龄. 普通心理学[M]. 北京:北京师范大学出版社, 2004.
[8] Li L, Li A, Hao B B, et al. Predicting active users' personality based on micro-blogging behaviors[J]. PLoS One, 2014, 9(1):e84997.
[9] Liu X, Liu X, Sun J, et al. Proactive suicide prevention online (PSPO):Machine identification and crisis management for Chinese social media users with suicidal thoughts and behaviors[J]. Journal of Medical Internet Research, 2019(5):e11705.
[10] 张滨熠, 周阳, 赵楠, 等. 基于微博大数据下的社会心态分析——以"青岛天价虾"事件为例[J]. 城市与减灾, 2018(2):26-29.
[11] Tan Z Y, Liu X Y, Liu X Q, et al. Designing microblog direct messages to engage social media users with suicide ideation:Interview and survey study on Weibo[J]. Journal of Medical Internet Research, 2017, 19(12):1-13.
[12] Sun B L, Zhang Z, Liu X Y, et al. Self-esteem recognition based on gait pattern using kinect[J]. Gait & Posture, 2017(58):428-432.
